Curriculum

Tomorrow’s scientists will live out their careers at an interface between domain sciences, math, computation, and data visualization. Basic skills in research data management are rarely incorporated in lab curricula or undergraduate independent research projects, beyond maintaining a good lab notebook, yet these skills are critical to a successful research career.

A skillset that formalizes knowledge of the data lifecycle is desirable starting at the undergraduate level and carried through to graduation and beyond. Integrating data science modules into existing courses will help contextualize data usage with subject components and offer multiple iterations of data acquisition, cleaning, querying, analyzing, and reporting/visualizing. In the process students will be exposed to and become familiar with different types of publicly available data and open source analytical software.

Approach

1. Design modules that embed DSAV into a variety of undergraduate STEM courses. Here, we are working on the development of teaching modules that can be used in different class settings.  The gaol is to make data science a common part of the undergraduate experience and have the concepts used in the practices of exploring and analyzing data a regular practice.

2. Design stand-alone Certificate and Bachelors Programs in DSAV (Fall 2018)

3. Summer immersion program (Fall 2018)

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